PID control algorithm is one of the simplest
one to control a system. It is well implemented to
control various kind of system, one of them is the
quadrotor. However, it is obviously that this is
not the best solution and there are many other
controller which is promising and need to be
tested with the real things, not only by using the
Simulink models. IB controller is one of them,
which not only increases the robustness of the
quadrotor but also has a very good tracking
ability.
The result with the SITL simulation proves
that a modified firmware built by ArduPilot is
ready to test in real flight, which will give more
results, especially the real response of the control
board in real environment. By understanding the
pros and cons of each controller in specific
situation, a changeable controller, which is the
optimized controller, can be implemented for a
real quadrotor in the future.

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SCIENCE & TECHNOLOGY DEVELOPMENT, Vol 18, No.K7- 2015
Trang 170
Results and comparision between
different control algorithms for a
quadrotor using ArduPilot framework
Nguyen Anh Quang1
Emmanuel Grolleau2
Ngo Khanh Hieu1
1Ho Chi Minh City University of Technology,VNU-HCMUT
2LIAS, ISAE – ENSMA, France
(Manuscript Received on July 13th, 2015; Manuscript Revised October 16th, 2015)
ABSTRACT:
Determining the most suitable control
algorithm for a system is not an easy task. In
theory, each controller has its own
advantages and disadvantages comparing
to the others. However, in the real world, the
behavior of the controller also depends on
many other factors such as the calculating
ability of the control board, the accuracy of
the sensors, the way the hardware
communicate with the others, etc. In order to
find the pros and cons of each control
algorithm in the real world, each of them has
to be tested and then comparing their
results. This article presents a simple way to
test the behavior of various control
algorithms, with the quadrotor as the control
target and ArduPilot is the framework to
create the firmware carrying multi
controllers. At the end of this article, the
results of 3 control algorithms: Original PID
of ArduPilot, new developed PID and Integral
Backstepping will be presented and
compared. These data is created by using
Software In The Loop simulation (SITL), a
tool provided by ArduPilot to test the new
developed firmware.
Key words: ArduPilot, control algorithm, quadrotor, PID, Integral Backstepping
1. INTRODUCTION
Quadrotor is a six degree of freedoms
system which is only controlled by four fixed-
pitch equally-space rotors. In other words, even
though the mechanically design is simple [1], this
flying system is underactuated. The calculating
for controlling this system will therefore be
complicated. In theory, there are several control
algorithms which is suitable for a quadrotor such
as PID, Adaptive Control, Integral Backstepping
[2], nonlinear H∞ [3] or LQR controllers [4].
.However, there is no optimized controller for
this system. Since each method has its pros and
cons, the control algorithm for a quadrotor should
base on the environment of the real system as
well as its objectives. A controller, which can has
the ability to change the control method in
specific situations and desires will therefore be
the best solution in this case. In order to
experience the pros and cons of control methods,
we decide to use the ArduPilot, a very popular
framework used to create the firmware for the
autonomous unmanned system, as the framework
TAÏP CHÍ PHAÙT TRIEÅN KH&CN, TAÄP 18, SOÁ K7- 2015
Trang 171
to develop a module to integrate new control
algorithms for the quadrotor. Using SITL
simulation, we can verify that this module is good
enough for taking the experiment with the real
system and give us some ideas about the good
and bad side of the integrated controllers.
2. QUADROTOR – FROM EQUATIONS TO
INTEGRATED CODE
By default, there are several ways to create
the integrated code to control a system. This
article will present a solution suitable for
complex systems, in this case a quadrotor. The
basic of this solution is based on new tools which
can transfer Simulink models into C code, as can
be seen in figure 1.
Figure 1. From theoay to C code
Using the Euler-Lagrange methods, the
motion of the quadrotor plus frame is described
by the following equations [6]:
2 2
1 2 3 4 4 2
2 2
1 2 3 4 3 1
2 2 2 2
1 2 3 4
y z r
x x x
x z r
y y y
x y
z z
I I J lb
I I I
I I J lb
I I I
I I d
I I
(1)
The controlled targets of the equation (1) are
the Euler angles roll, pitch, yaw, which is
represented by , and f q y ; meanwhile, the
control outputs are the angular speed of the four
motors. In order to test the equations above, they
has been described by MATLAB Simulink
model and then put in blocks with the principle
shown in figure 2.
Figure 2. Blocks for the Simulink Model in
MATLAB
Figure 3. Simulink model for new PID
controller
Based on the flight path or the inputs values
from the users, the desired Euler angles will be
created and then converted into the angular speed
of each motor of the quadrotor. The Controller
block can contain any kind of controller, as long
as developers can describe it with Simulink
model. This Controller block is then handled by
the Gene-auto to create the necessary code. For
example, figure 3 and figure 4 shows the
Simulink model for the PID controller
controlling the outputs of the quadrotor and the C
code generated by Gene-auto.
SCIENCE & TECHNOLOGY DEVELOPMENT, Vol 18, No.K7- 2015
Trang 172
Figure 4. Code generated with GeneAuto
3. ARDUPILOT AND MODULE TO EMBED
NEW CONTROLLERS
ArduPilot is one of the popular framework
to create the firmware for an autonomous
unmanned vehicle. One of the most important
benefits of this framework comparing to others is
that it has a multilayer structure, as described in
figure figure 5. With this structure, this
framework can support multiple control boards.
Figure 5. Multilayer structure of ArduPilot
In Vietnam, this framework is also very
famous for developers, who have been familiar
with boards such as APM2.5 or APM2.6 and the
ground control station called Mission Planner.
However, this article will focus more about the
code and the modified to make this framework
become multi-controllers, which is useful for
users in the future.
The idea of this solution is simple, shown in
figure 6. By default, ArduPilot has an original
PID controller system, which control the rate of
change of the Euler angles. In other words, this
system handles the , and f q y by controlling
, and f q y& & &, PID control algorithm is used to
make the real values of the system become as
close as possible with the desired values. A new
module has been created and embedded into the
framework. The principle of the new add-in
module is that users can change the using
controller with just a single switch. By
minimizing the modification, this module can use
all of the advantages of the original code, for
example the multilayer structure and the
readiness for specific control boards, and still
made the ArduPilot become a multi-controller
framework.
As can be seen in this figure, if users choose
to use the original controller, which is the default
PID controller of ArduPilot mentioned above,
nothing will change and the calculation process
will be the same with the original code. However,
when users decide to use a new controller, the
calculating process will be changed and new
control outputs will be generated based on the
chosen control algorithm.
Figure 6. General idea of the new add-in module
4. ARDUPILOT AND CREATED MODULE
TO EMBED NEW CONTROLLERS
This article will focus on introducing two of
the control algorithms which have been
successfully embedded into ArduPilot
framework using the solution above.
TAÏP CHÍ PHAÙT TRIEÅN KH&CN, TAÄP 18, SOÁ K7- 2015
Trang 173
Figure 7. ArduPilot original PID controller
These results not only confirm the
availability of the add-in module but also gives
the comparison required to get the pros and cons
of each controller with the quadrotor.
Unlike the original PID controls the rate of
change of the Euler angles , and f q y& & &, the new
PID controller in figure 3 calculates the angular
speed of motors based on the Euler angles
, and f q y . The differences between the two
control algorithms are small, however, by
changing from the rate of change into the Euler
angles, new PID controller reduces the amount of
calculation required. This conclusion can be
concluded according to the comparison between
figure 7 and figure 3 above. In fact, as mentioned,
both control algorithm has its benefits and
drawbacks, and from the results shown in part 4,
the original controller has better responses than
the new PID controller.
“Backstepping control is a recursive
algorithms that breaks down the controller into
steps and progressively stabilizes each system”
[2]. By adding an Integrator into the system to
increase its robustness, the controller will
become Integral Backstepping, which will not
only work well with the dynamic of a quadrotor
[5] but also make it is more stable with the
disturbances [2]. Figure 8 introduces the IB
controller used for a quadrotor.
With the definitions in equations (2), the
motion equations of the quadrotor in case using
the Integral Backstepping control algorithm will
become equation (3). In equations (2), the values
of c and λ are the control constants of the control
algorithm; meanwhile, e is the error between the
desired values and the real Euler angles
respectively [6].
Figure 8. IB controller for a quadrotor
SCIENCE & TECHNOLOGY DEVELOPMENT, Vol 18, No.K7- 2015
Trang 174
1 2 3 4
2
1 7 4 7 7 8 8 7 4 4
2
2 1 1 1 1 2 2 1 1 1
2
3 3 2 3 3 4 4
cos sin cos sin sin
cos sin sin sin cos
1
cos cos
1
1
x
y
r
d
y z r
dx r
x x
y
u
u
mU g c e c c e c z
I I JU I c e c c e c
I I
U I c e c c e c
3 2 2
2
4 5 3 5 5 6 6 5 3 31
z x r
d r
y y
x y
dz
z
I I J
I I
I I
U I c e c c e c
I
(2)
2
3
4
1
1
1 cos cos
y z r
r
x x x
z x r
r
y y y
x y
z z
x
y
I I J U
I I I
I I UJ
I I I
I I U
I I
UX u
m
U
Y u
m
U
Z g
m
(3)
By using MATLAB Simulink, the model of
the Integral Backstepping can be described as in
figure 9 and then embedded into the framework
of ArduPilot. Users can choose to use this
algorithm by using the new add-in module.
5. RESULTS WITH NEW PID
CONTROLLER IN SOFTWARE IN THE
LOOP SIMULATION (SITL)
Software In The Loop is a tool provided by
ArduPilot to developers, which can be used to
test new firmware and new modifications, in this
case a new module to embed new controllers.
Unlike Hardware In The Loop (HITL), which
uses the virtual inputs with the real board to
experience the the response of the real Hardware
in some specific cases, SITL uses both virtual
environment and hardware. Table 1 gives a
simple comparison between two types of
simulation.
Table 1. HITL and SITL comparisons
Using SITL with the same flight path, figure
10 and figure 11 introduces the results with the
original PID controller of ArduPilot and the new
PID controller.
TAÏP CHÍ PHAÙT TRIEÅN KH&CN, TAÄP 18, SOÁ K7- 2015
Trang 175
Figure 9. Integral Backstepping MATLAB Simulink model
Figure 10. Pitch (left) and yaw (right) disired and response results with original and new PID
Figure 11. Tracking result with old PID (left) and new PID (right)
SCIENCE & TECHNOLOGY DEVELOPMENT, Vol 18, No.K7- 2015
Trang 176
Figure 12. Tracking result with old PID (right) and IB controller (left)
The tracking ability of the new PID
controller is as good as the old one (figure 10).
Although there are still some errors, the new PID
control algorithm still can drive the quadrotor
back to the desired flight path. Figure 11 gives a
more detail result. When comparing between the
desired Euler angles and the response ones, it can
be seen that the new PID controller results follow
really close with the desired values. It is not as
good as the old one, however it can be concluded
that the new PID is steady enough for a real test.
6. RESULTS WITH INTEGRAL
BACKSTEPPING IN SOFTWARE IN THE
LOOP SIMULATION (SITL)
Using the same flight path with the Integral
Backstepping, figure 12 and figure 13
demonstrate the results. Although the IB
controller can trace the flight path well, there are
some fluctuations as can be seen in figure 13.
Nevertheless, as mentioned in the theory, IB
controller has high robustness, which make the
response of the system follow closely the desired
values. Figure 14 give a more detail look for this
conclusion.
Figure 13. Pitch deired and response resutls with
original PID and IB
7. CONCLUSIONS
With the results above, it is clearly that
using the existence, open-source framework is
one of the best solution to testing new control
theory new modifications. With suitable changes,
for example creating new add-in modules for
necessary requirements, the modified firmware
can use both the ready-to use structure of the
original firmware and the benefits of the new
code.
TAÏP CHÍ PHAÙT TRIEÅN KH&CN, TAÄP 18, SOÁ K7- 2015
Trang 177
Figure 14. IB controller and new PID controller
PID control algorithm is one of the simplest
one to control a system. It is well implemented to
control various kind of system, one of them is the
quadrotor. However, it is obviously that this is
not the best solution and there are many other
controller which is promising and need to be
tested with the real things, not only by using the
Simulink models. IB controller is one of them,
which not only increases the robustness of the
quadrotor but also has a very good tracking
ability.
The result with the SITL simulation proves
that a modified firmware built by ArduPilot is
ready to test in real flight, which will give more
results, especially the real response of the control
board in real environment. By understanding the
pros and cons of each controller in specific
situation, a changeable controller, which is the
optimized controller, can be implemented for a
real quadrotor in the future.
So sánh và đánh giá khả năng điều
khiển máy bay bốn chong chóng với các
thuật toán khác nhau trên nền tảng
ArduPilot
Nguyễn Quang Anh1
Emmanuel Grolleau2
Ngô Khánh Hiếu1
1Ho Chi Minh City University of Technology, VNU-HCMUT
2LIAS, ISAE – ENSMA, France
TÓM TẮT:
Trên lí thuyết, mỗi thuật toán điều khiển
đều có những ưu và nhược điểm đặc trưng.
Trên thực tế, khả năng điều khiển cơ hệ còn
phụ thuộc vào nhiều yếu tố khác của cơ hệ
và hệ thống điều khiển. Trong trường hợp
này, cách duy nhất để xác định chính xác
SCIENCE & TECHNOLOGY DEVELOPMENT, Vol 18, No.K7- 2015
Trang 178
phản ứng của một hệ điều khiển là thử
nghiệm trên hệ thống thực và đánh giá kết
quả. Dựa trên việc sử dụng một hệ thống
phức tạp là máy bay bốn chong chóng, bài
báo này trình bày phương pháp đưa các hệ
điều khiển khác nhau vào ArduPilot. Mô
phỏng Software In The Loop đã được sử
dụng để thực nghiệm 3 thuật điều khiển khác
nhau: PID gốc của ArduPilot, PID tự phát
triển và Integral Backstepping. Qua đó,
ngoài việc xác định khả năng của hệ điều
khiển, bài báo cũng nêu lên một vài kết quả
bước đầu với các hệ điều khiển này, xác
nhận lại lí thuyết đã biết của các thuật toán
này, đồng thời là bước quan trọng để xác lập
các hệ số điều khiển trước khi tiến hành bay
thực.
Keyword: ArduPilot, thuật điều khiển quadrotor, PID, Integral Backstepping
REFERENCES
[1]. M. J. Cutler, Design and Control of an
Autonomous Variable-Pitch Quadrotor
Helicopter, M.Sc Thesis, Massachusetts
Institute of Technology, 2012.
[2]. S. J. Andrew Zulu, "A Review of Control
Algorithms for Autonomous Quadrotors"
Open Journal of Applied Sciences, pp. 547-
556, 2014.
[3]. G. Raffo, M.G.Ortega and F.R.Rubio, "An
integral predictive/nonlinear H∞ control
structure for a quadrotor helicopter"
Automatica, vol. 46, pp. 29-39, 2010.
[4]. S. Bouabdallah, A. Noth et R. Siegwart,
«PID vs LQ control techniques applied to an
indoor micro quadrotor» IEEE/RSJ
Internation Conference on Intelligent
Robots and Systems, vol. 3, pp. 2451-2456,
2004.
[5]. Bouadallah.S et al, «Full control of a
quadrotor» Intelligent Robots and Systems
2007. IROS 2007, pp. 153-158, 2007.
[6]. A. Benito, «Flight Control and Navigation
of a Quadcopter» Poitiers, 2014.

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